Endometrioid endometrial adenocarcinoma in a premenopausal woman with multiple organ metastases

Exploring the Potential Link between PFAS Exposure and Endometrial Cancer: A Review of Environmental and Sociodemographic Factors

This exploratory narrative review paper delves into the intricate interplay between per- and polyfluoroalkyl substances (PFAS) exposure, sociodemographic factors, and the influence of stressors in the context of endometrial cancer. PFAS, ubiquitous environmental contaminants notorious for their persistence in the ecosystem, have garnered attention for their potential to disrupt endocrine systems and provoke immune responses. We comprehensively examine the various sources of PFAS exposure, encompassing household items, water, air, and soil, thus shedding light on the multifaceted routes through which individuals encounter these compounds. Furthermore, we explore the influence of sociodemographic factors, such as income, education, occupation, ethnicity/race, and geographical location and their relationship to endometrial cancer risk. We also investigated the role of stress on PFAS exposure and endometrial cancer risk. The results revealed a significant impact of sociodemographic factors on both PFAS levels and endometrial cancer risk. Stress emerged as a notable contributing factor influencing PFAS exposure and the development of endometrial cancer, further emphasizing the importance of stress management practices for overall well-being. By synthesizing evidence from diverse fields, this review underscores the need for interdisciplinary research and targeted interventions to comprehensively address the complex relationship between PFAS, sociodemographic factors, stressors, and endometrial cancer.

Immunohistochemical Expression of BCL-2 in Endometrial Carcinoma and Its Comparison With Hormone Receptor Status and Epidermal Growth Factor

BACKGROUND

Endometrial carcinoma is the most common malignant tumor of the female genital tract with increasing incidence in developed countries. In the era of targeted therapy, immunohistochemical markers play an important role in the treatment and prognosis of endometrial carcinoma. The aim of the study was to study the immunohistochemical expression of B-cell lymphoma 2 (BCL-2) in endometrial carcinoma and to study the correlation of BCL-2 expression with hormone receptor status and transforming growth factor receptors in endometrial carcinoma.

METHODS

Endometrial carcinoma reported between the period from January 2010 to December 2014 in the department of pathology of this institute was considered in the study. The study included cases of endometrial carcinoma reported on both curetting and hysterectomy specimens. In the samples where both curetting and hysterectomy were received only hysterectomy blocks were included and the curetting was excluded.

RESULTS

The total number of malignancies reported during this period was 3478. Of these 3478 malignancies, 59 were endometrial carcinomas with an incidence of 1.6%. Out of 59 endometrial carcinomas, 46 cases were diagnosed on hysterectomy specimens and 13 cases were diagnosed on endometrial curetting biopsies.

CONCLUSION

The positive expressions of estrogen receptor (ER) and progesterone receptor (PR) in endometrial carcinoma suggest that steroid receptor studies may be of potential benefit in the management of some patients with endometrial carcinoma.

Machine Learning for Endometrial Cancer Prediction and Prognostication

Endometrial cancer (EC) is a prevalent uterine cancer that remains a major contributor to cancer-associated morbidity and mortality. EC diagnosed at advanced stages shows a poor therapeutic response. The clinically utilized EC diagnostic approaches are costly, time-consuming, and are not readily available to all patients. The rapid growth in computational biology has enticed substantial research attention from both data scientists and oncologists, leading to the development of rapid and cost-effective computer-aided cancer surveillance systems. Machine learning (ML), a subcategory of artificial intelligence, provides opportunities for drug discovery, early cancer diagnosis, effective treatment, and choice of treatment modalities. The application of ML approaches in EC diagnosis, therapies, and prognosis may be particularly relevant. Considering the significance of customized treatment and the growing trend of using ML approaches in cancer prediction and monitoring, a critical survey of ML utility in EC may provide impetus research in EC and assist oncologists, molecular biologists, biomedical engineers, and bioinformaticians to further collaborative research in EC. In this review, an overview of EC along with risk factors and diagnostic methods is discussed, followed by a comprehensive analysis of the potential ML modalities for prevention, screening, detection, and prognosis of EC patients.

High-intermediate risk endometrial cancer: moving toward a molecularly based risk assessment profile

In the USA, endometrial cancer (EMCA) incidence is increasing as the risk factors of obesity, diabetes, and hypertension become more prevalent. Although most EMCA is detected at an early stage and surgical intervention is curative, a subset of patients termed 'high-intermediate risk' (H-IR) experience an increased rate of recurrence. Unfortunately, adjuvant therapies in patients with H-IR EMCA have yet to increase overall survival. Historically, stratification of these patients from their low-risk counterparts incorporated clinical and pathologic findings. However, due to developments in molecular testing and genomic sequencing, tumor biomarkers are now being incorporated into the risk-assessment criteria in the hope of finding molecular profile(s) that could highlight treatment regimens that will increase patient survival. Since modern research aims to accurately identify patients with a higher risk of recurrence and develop effective interventions to improve patient survival, these molecular-based analyses could allow for an enhanced understanding of a patient's true risk of recurrence to facilitate the rise of personalized medicine. This review summarizes key clinical trials and recent advances in molecular and genomic profiles that have influenced current treatment regimens for patients with H-IR EMCA and laid the foundation for subsequent research.

Combined Open and Endoscopic Endonasal Skull Base Resection of a Rare Endometrial Carcinoma Metastasis

In the absence of significant extracranial disease, patients with solitary brain metastases have shown benefit with resection. Brain lesions due to endometrial cancer are uncommon, and the only described skull base involvement is limited to the pituitary gland. We report the case of a 60-year-old female with endometrial cancer who presented with weeks of right cheek pain and numbness that was accompanied by headaches. We describe the magnetic resonance imaging (MRI) findings and surgical resection of a solitary endometrial metastasis involving the infratemporal fossa, middle fossa, cavernous sinus, trigeminal nerve, and nasal sinuses. Due to extensive nasal and lateral involvement, a combined open and endoscopic approach was planned. The patient was discharged home without complication. She underwent adjuvant radiotherapy. Despite its suspected indolent course, intracranial endometrial adenocarcinoma metastases are gaining higher prevalence. This case report documents the first direct neural spread of an endometrial primary, and highlights the potential for extra-axial sites of metastasis.